def test_batch_metrics_visdom(self, mock_visdom, mock_writer, _):
mock_writer.return_value = Mock()
mock_writer.return_value.add_scalar = Mock()
state = {
torchbearer.MODEL: nn.Sequential(nn.Conv2d(3, 3, 3)),
torchbearer.EPOCH: 0,
torchbearer.METRICS: {
'test': 1
},
torchbearer.BATCH: 0,
torchbearer.TRAIN_STEPS: 0
}
tboard = TensorBoard(visdom=True,
write_batch_metrics=True,
write_epoch_metrics=False)
tboard.on_start(state)
tboard.on_start_epoch(state)
tboard.on_step_training(state)
mock_writer.return_value.add_scalar.assert_called_once_with(
'test', 1, 0, main_tag='batch')
mock_writer.return_value.add_scalar.reset_mock()
tboard.on_step_validation(state)
mock_writer.return_value.add_scalar.assert_called_once_with(
'test', 1, 0, main_tag='batch')
tboard.on_end_epoch(state)
tboard.on_end(state)
def test_batch_metrics(self, mock_board):
mock_board.return_value = Mock()
mock_board.return_value.add_scalar = Mock()
state = {torchbearer.EPOCH: 0, torchbearer.METRICS: {'test': 1}, torchbearer.BATCH: 0}
tboard = TensorBoard(write_batch_metrics=True, write_epoch_metrics=False)
tboard.on_start_epoch(state)
tboard.on_step_training(state)
mock_board.return_value.add_scalar.assert_called_once_with('batch/test', 1, 0)
mock_board.return_value.add_scalar.reset_mock()
tboard.on_step_validation(state)
mock_board.return_value.add_scalar.assert_called_once_with('batch/test', 1, 0)
def test_batch_metrics(self, mock_board):
mock_board.return_value = Mock()
mock_board.return_value.add_scalar = Mock()
state = {
torchbearer.EPOCH: 0,
torchbearer.METRICS: {
'test': 1
},
torchbearer.BATCH: 0
}
tboard = TensorBoard(write_batch_metrics=True,
write_epoch_metrics=False)
tboard.on_start_epoch(state)
tboard.on_step_training(state)
mock_board.return_value.add_scalar.assert_called_once_with(
'batch/test', 1, 0)
mock_board.return_value.add_scalar.reset_mock()
tboard.on_step_validation(state)
mock_board.return_value.add_scalar.assert_called_once_with(
'batch/test', 1, 0)
